Abstract
In this paper, we analyze the celebrated EM algorithm from the point of view of proximal point algorithms. More precisely, we study a new type of generalization of the EM procedure introduced in [Chretien and Hero (1998)] and called Kullback-proximal algorithms. The proximal framework allows us to prove new results concerning the cluster points. An essential contribution is a detailed analysis of the case where some cluster points lie on the boundary of the parameter space. © 2008 EDP Sciences SMAI.
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Chrétien, S., & Hero, A. O. (2008). On EM algorithms and their proximal generalizations. ESAIM - Probability and Statistics, 12, 308–326. https://doi.org/10.1051/ps:2007041
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